Job Title: Associate Fraud Strategy Data Scientist

Location: San Jose, CA

Duration: 12 Months

Job Description:

We’d love to chat if you have:

• Maximum 2 years of experience in risk analytics, data analysis, and data science within relevant industry experience in eCommerce, online payments, user trust/risk/fraud, or investigation/product abuse.
• Bachelor’s degree in Data Analytics, Data Science, Mathematics, Statistics, Data Mining or related field or equivalent practical experience
• Experience using statistics and data science to solve complex business problems
• Proficiency in SQL, Python, Excel including key data science libraries
• Proficiency in data visualization including Tableau
• Experience working with large datasets
• Ability to clearly communicate complex results to technical experts, business partners, and executives including development of dashboards and visualizations, ie Tableau.
• Comfortable with ambiguity and yet able to steer analytics projects toward clear business goals, testable hypotheses, and action-oriented outcomes
• Demonstrated analytical thinking through data-driven decisions, as well as the technical know-how, and ability to work with your team to make a big impact.
• Desirable to have experience or aptitude solving problems related to risk using data science and analytics
• Bonus: Experience with AWS, knowledge of fraud investigations, payment rule systems, working with ML teams, fraud typologies

Key Job Functions

• Design rules to detect/mitigate fraud
• Develop python scripts and models that support strategies
• Investigate novel/large cases
• Identify root cause
• Set strategy for different risk types
• Work with product/engineering to improvement control capabilities
• Develop and present strategies and guide execution

MUST HAVE:

• Maximum 2 years of experience in risk analytics, data analysis, and data science within relevant industry experience in eCommerce, online payments, user trust/risk/fraud, or investigation/product abuse.
• Bachelor’s degree in Data Analytics, Data Science, Mathematics, Statistics, Data Mining or related field or equivalent practical experience.
• Experience using statistics and data science to solve complex business problems.
• Experience in SQL, Python, Excel including key data science libraries.
• Experience applying statistics and data science to tackle intricate business challenges especially in Fraud mitigation.
• Experience in data visualization including Tableau.
• Experience working with large datasets.